Social Sciences
Source: http://book.openingscience.org/vision/altmetrics.html
communication, in particular since the number of available faculty
positions and grants has far exceeded the number of applications. Peer
review still plays a critical role in evaluating science, but
citation-based bibliometric indicators are becoming increasingly
important. This chapter looks at a novel set of indicators that can
complement both citation analysis and peer review. Altmetrics use
indicators gathered in the real-time Social Web to provide immediate
feedback about scholarly works. We describe the most important
altmetrics and provide a critical assessment of their value and
limitations.
scholarly communication. In the last 25 years, we have seen a shift from
individual qualitative assessment by peers to systematic quantitative
assessment using citation analysis of journal articles. Arguably the
impact of research can not be quantified, and citation analysis falls
short of a comprehensive analysis, but the journal as a filter for
relevant scholarly content and the Journal Impact Factor as a tool to
quantify the relevance of journals are at the core of how research is
communicated and evaluated today.
The central role of the journal (to distribute, filter, and help
evaluate scholarly content) has dramatically changed with the shift from
print to electronic publishing, and is no longer appropriate for the
assessment of impact. We can look at citations of individual articles,
and at other measures of impact using usage stats and the Social Web.
Moreover, impact assessment does not have to be confined to journal
articles; research outputs such as data publication can also be
assessed.
Altmetrics is a young discipline that looks at new metrics based on
the Social Web for analyzing scholarship. Altmetrics are complementary
to the citation-based filters which we have relied upon for the past 50
years and try to overcome some of their shortcomings: citations are slow
to accumulate, and often miss new forms of scholarly content such as
datasets, software, and research blogs (Priem et al. 2012a).
Altmetrics are challenging this established system, and are therefore
seen by many as either an opportunity or a threat to the current system
of scholarly communication. This potential makes altmetrics both
fascinating and challenging, as many discussions about altmetrics are
often intermixed with other ideas about how to change scholarly
communication.
Bibliometrics is a major subdiscipline of
scientometrics which measures the impact of scientific publications.
Citation analysis is the most popular application of bibliometrics.
Usage-based metrics use usage data (pageviews,
document downloads, etc.) to assess scholarly impact. The concept was
popularized by the COUNTER (Counting Online Usage of NeTworked
Electronic Resources) and MESUR (MEtrics from Scholarly Usage of
Resources) projects.
Altmetrics is the creation and study of new metrics based on the Social Web for analyzing and informing scholarship (Altmetrics Manifesto).
Altmetrics is a sub-discipline of scientometrics. Altmetrics typically
looks at individual research outputs, including journal articles or
datasets.
Article-level metrics are a comprehensive and multidimensional suite of transparent and established metrics at the article level (see PLOS Article-Level Metrics).
They collect and provide metrics for individual articles, rather than
aggregating them per journal. Article-level metrics include citations,
usage data, and altmetrics. Article-level metrics are typically
associated with the publisher Public Library of Science (PLOS), who
introduced them for all of their articles in 2009. Altmetrics and
article-level metrics are sometimes used interchangeably, but there are
important differences:
Author-level metrics aggregate the metrics of all research by a specific author. Metrics can also be aggregated by institution, discipline, etc.
Post-publication peer review is the process whereby
scientific studies are absorbed into the body of knowledge (BMJ Group
2011). This definition is much broader and does not just include
activities that are traditionally described as peer review. In contrast
to metrics, the focus is on the discussion of a paper in comments, blog
posts, and citations. A broader term with similar meaning is
post-publication activity.
advocating social bookmarking tools for post-publication peer review.
Neylon and Wu described the PLOS Article-Level Metrics service launched
in 2009 in an article published the same year. Priem and Hemminger
published an article in July 2010 that describes scientometrics 2.0 and
called for new metrics based on Web 2.0 tools. Groth and Gurney (???)
studied chemistry science blogging about scholarly papers and presented
their findings at the Web Science Conference 2010. The Altmetrics
manifesto was published in October 2010 by Jason Priem, Dario
Taraborelli, Paul Groth and Cameron Neylon.
ReaderMeter is a web service that tracks the number of Mendeley
readers of all papers of a particular author. ReaderMeter was launched
in late 2010 and is the first working altmetrics service. The first
altmetrics workshop was was altmetrics11, held at the ACM Web Science Conference 2011 Workshop
in June 2011. Hackathons are an important part of altmetrics history: a
working prototype for Total Impact (now ImpactStory) was put together
at the Beyond Impact conference in May 2011, and the idea of the
ScienceCard project started at the Science Online London conference in
September 2011. Three of the 11 finalists of the Mendeley/PLOS Binary
Battle programming contest in September 2011 were altmetrics
applications. In 2012, we saw the launch of several altmetrics services,
more publishers implementing altmetrics for their journal articles, and
an increasing number of presentations and workshops dedicated to
altmetrics.
the ACM Web Science conference were held: June 2011 in Koblenz, Germany
and June 2012 in Evanston, IL.
PLOS ONE launched the Altmetrics collection in October 2012, with initially 7 research articles published since June 2009.
Much early altmetrics research has examined reference managers,
particularly Mendeley and CiteULike. Li et al. (2011) found 92% of
Nature and Science articles in their sample had been bookmarked by one
or more Mendeley users, and 60% by one or more CiteULike users. Bar-Ilan
(2012) showed 97% coverage of recent JASIST articles in Mendeley.
Priem, Piwowar and Hemminger (2012) reported that the coverage of
articles published in the PLOS journals was 80% in Mendeley and 31% in
CiteULike. Sampling 1,397 F1000 Genomics and Genetics papers, Li and
Thelwall (2012) found that 1,389 of those had Mendeley bookmarks.
Studies have consistently found moderate correlation between
reference manager bookmarks and Web of Science (WoS) citations. Li et
al. (2011) showed r=0.55 of Mendeley and r=0.34 of CiteULike readers
with WoS citations respectively. Weller and Peters (2012) report similar
correlation values for a different article set between Mendeley,
CiteULike, BibSonomy, and Scopus. Bar-Ilan (2012) found a correlation of
r=0.46 between Mendeley readership counts and WoS citations for
articles in JASIST. User-citation correlations for sampled Nature and
Science publications were 0.56 (Li et al. 2011); Priem et al. (2012b)
report a correlation of 0.5 between WoS citations and Mendeley users
articles published by the open-access publisher PLOS.
Twitter has also attracted significant interest from altmetrics researchers. Priem and Costello (2010) and Priem et al. (2011) report that scholars use Twitter as a professional medium for discussing articles, while Eysenbach (2011)
found that highly-tweeted articles were 11 times more likely become
highly-cited later. Analyzing the use of Twitter during scientific
conferences, Weller and Puschmann (2011)
and Letierce et al. (2010) report that there was discipline-specific
tweeting behavior regarding topic and number of tweets, as well as
references to different document types including journal articles,
blogs, and slides. Other sources have examined additional data sources
besides reference managers and Twitter, investigating examined citation
from Wikipedia articles (Nielsen 2007) and blogs (???; Shema et al. 2012) as sources of alternative impact data.
clear that relying on the journal as a filter is no longer an
appropriate strategy. Altmetrics have the potential to help in the
discovery process, especially if combined with more traditional
keyword-based search strategies, and with the social network information
of the person seeking information. The advantage over citation based
metrics is that we don?t have to wait years before we can see meaningful
numbers. The free Altmetric PLOS Impact Explorer
is an example for a discovery tool based on altmetrics and highlights
recently published PLOS papers with a lot of social media activity.
Altmetric.com also provides a commercial service for content from other
publishers.
research, in particular if the research outputs are not journal
articles, but data sets, software, etc., and if the impact is best
demonstrated in metrics other than citations. ImpactStory
focuses on this use case. Often creators of web-native scholarly
products like datasets, software, and blog posts are hard pressed to
demonstrate the impact of their work, given a reward system built for a
paper-based scholarly publishing world. In these cases, ImpactStory
helps to provide data to establish the impacts of these products and
allow forward-thinking researcher. ImpactStory also gathers altmetrics
to demonstrate wider impacts of traditional products, tracking their
impact through both traditional citations and novel altmetrics.
trends over time and/or across funding programs, disciplines, etc. This
is an area that the typical researchers is usually less interested in,
but is important for strategic decisions by departments, universities,
funding organizations, publishers, and others. This area has been
dominated by large commercial bibliographic databases such as Web of
Science or Scopus, using citation data. Plum Analytics is a new service that also provide altmetrics and is focusing on universities. The publisher PLOS makes a comprehensive set of citations, usage data and altmetrics available for all articles they published.
including inappropriate uses such as using the Journal Impact Factor to
evaluate publications of individual researchers. Before altmetrics can
be used for evaluation, the following questions need to be addressed:
scientometrics for evaluation, whereas the last three questions are more
specific for altmetrics. All these issues can be solved, but it will
probably take some time before altmetrics can be reasonably used for
evaluation.
Author-level metrics can also include citations and usage stats.
Citations are a more established metric for impact evaluation, and
citations based on individual articles are much more meaningful than the
metrics for the journal that a researcher has published in. The
Hirsch-Index (or h index, Hirsch 2005) is a popular metric to quantify
an individual?s scientific research output. The h index is defined as
the number of papers with citation number ?h, e.g. an h index of 15 means a researcher has published at least 15 papers that have been cited at least 15 times.
the most important metrics and providers are listed below. Not all
metrics measure scholarly impact, some of them are indicators of
attention, and in rare cases self-promotion. Some metrics are good
indicators of activity by scholars (e.g. citations or Mendeley
bookmarks), whereas other metrics reflect the attention by the general
public (e.g. Facebook or HTML views).
Metrics describe different activities: usage stats look at the
initial activity of reading the abstract and downloading the paper,
whereas citations are the result of much more work, they therefore
account for less than 0.5% of all HTML views. Altmetrics tries to
capture the activities that happen between viewing a paper and citing
it, from saving an article to informal online discussions.
articles with Mendeley bookmarks is similar to the number of articles
that have ciations. Mendeley provides information about the number of
readers and groups. In contrast to CiteULike no usernames for readers
are provided, but Mendeley provides basic information regarding
demographics such as country and academic position. Mendeley is a social
bookmarking tool used by scholars and the metrics probably reflect an
important scholarly activity - adding a downloaded article to a
reference manager.
Mendeley and without reference manager functionality. One advantage over
Mendeley is that usernames and dates for all sharing events are
publicly available, making it easier to explore the the bookmarking
activity over time.
Twitter
Collecting tweets linking to scholarly papers is challenging, because
they are only stored for short periods of time (typically around 7
days). There is a lot of Twitter activity around papers, and only a
small fraction is from the authors and/or journal. With some journals up
to 90% of articles are tweeted, the number for new PLOS journal
articles is currently at about 50%. The Twitter activity typically peeks
a few days after publication, and probably reflects attention rather
than impact.
Facebook
Facebook is almost as popular as Twitter with regards to scholarly
content, and provides a wider variety of interactions (likes, shares and
comments). Facebook activity is a good indicator for public interest in
a scholarly article and correlates more with HTML views than PDF
downloads.
by Dario Taraborelli and Daniel Mietchen calculates the number of
Wikipedia links per publisher. In the English Wikipedia the most
frequently cited publisher is Elsevier with close to 35,000 links. In
addition to Wikipedia pages, links to scholarly articles are also found
on user and file pages.
difficult to track. Many science bloggers use a blog aggregator,
Research Blogging, Nature Blogs and ScienceSeeker being the most popular
ones. The number of scholarly articles discussed in blog posts is small
(e.g. less than 5% of all PLOS articles), but they provide great
background information and can sometimes generate a lot of secondary
activity around the original paper (both social media activity and
downloads).
number of service providers. This will most likely change in the near
future, as more organizations become interested both in analyzing
altmetrics for their content (publishers, universities, funders) or for
providing altmetrics as a service.
The open access publisher Public Library of Science (PLOS)
was the first organization to routinely provide altmetrics on a large
number of scholarly articles. The first version of their article-level
metrics service was started in March 2009, and PLOS currently provides
usage data, citations and social web activity from 13 different data
sources. The article-level metrics data are provided via an open API and as monthly public data dump.
Altmetric.com is a commercial start-up that started
in July 2011. They maintain a cluster of servers that watch social media
sites, newspapers and magazines for any mentions of scholarly articles.
The data are available to individual users and as service for
publishers.
ImpactStory is a non-profit service providing
altmetrics since late 2011. They provide both altmetrics and traditional
(citation) impact metrics for both traditional and web-native scholarly
products, and are designed to help researchers better share and be
rewarded for their complete impacts.
Plum Analytics is a start-up providing altmetrics
data to universities and libraries. They also provide usage stats and
citation data, and track research outputs beyond journal articles,
e.g. presentations, source code and datasets.
At this time it is unclear how the altmetrics community will develop
over the next few years. It is possible that one or a few dominant
commercial players emerge similar to the market for citations, that a
non-profit organization is collected these numbers for all stakeholders,
or that we see the development of a more distributed system with data
and service providers, similar to how usage data for articles are
distributed.
widely adopted. A big part of the challenge is the very nature of the
Social Web, which is much more difficult to analyze than traditional
scholarly citations.
altmetrics, but are hard to solve for evaluation tools. Altmetrics is
still a young discipline and the community is working hard on these and
other questions, including standards, anti-gaming mechanisms, and ways
to put metrics into context.
Hirsch, J.E., 2005. An index to quantify an individual?s scientific research output. Proceedings of the National Academy of Sciences, 102(46), pp.16569?16572. doi:10.1073/pnas.0507655102.
Bar-Ilan, J., 2012. JASIST@mendeley, Available at: http://altmetrics.org/altmetrics12/bar-ilan/.
ImpactStory, 2012. A new framework for altmetrics. ImpactStory blog. Available at: http://blog.impactstory.org/2012/09/14/31524247207/.
Letierce, J. et al., 2010. Using Twitter During an Academic Conference: The #iswc2009 Use-Case. In Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media. Available at: http://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/view/1523.
Li, X. & Thelwall, M., 2012. F1000, Mendeley and Traditional Bibliometric Indicators. Available at: http://sticonference.org/Proceedings/vol2/Li_F1000_541.pdf.
Li, X., Thelwall, M. & Giustini, D., 2011. Validating online reference managers for scholarly impact measurement. Scientometrics, 91(2), pp.461?471. doi:10.1007/s11192-011-0580-x.
Neylon, C. & Wu, S., 2009. Article-Level Metrics and the Evolution of Scientific Impact. PLoS Biology, 7(11), p.e1000242. doi:10.1371/journal.pbio.1000242.
Nielsen, F.A., 2007. Scientific citations in Wikipedia. First Monday, 12(8). Available at: http://firstmonday.org/article/view/1997/1872.
Priem, J. et al., 2010. altmetrics: a manifesto. altmetrics. Available at: http://altmetrics.org/manifesto/.
Priem, J. & Costello, K.L., 2010. How and why scholars cite on Twitter. Proceedings of the American Society for Information Science and Technology, 47(1), pp.1?4. doi:10.1002/meet.14504701201.
Priem, J., Costello, K.L. & Dzuba, 2011. Poster at Metrics 2011: Symposium on Informetric and Scientometric Research,
Priem, J., Groth, P. & Taraborelli, D., 2012. The Altmetrics Collection C. A. Ouzounis, ed. PLoS ONE, 7(11), p.e48753. doi:10.1371/journal.pone.0048753.
Priem, J. & Hemminger, B.M., 2010. Scientometrics 2.0: Toward new metrics of scholarly impact on the social web. First Monday, 15(7). Available at: http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2874/2570.
Priem, J., Piwowar, H.A. & Hemminger, B.M., 2012. Altmetrics in
the wild: Using social media to explore scholarly impact. Available at:
arXiv:1203.4745v1.
Shema, H., Bar-Ilan, J. & Thelwall, M., 2012. Research Blogs and
the Discussion of Scholarly Information C. A. Ouzounis, ed. PLoS ONE, 7(5), p.e35869. doi:10.1371/journal.pone.0035869.
Taraborelli, D., 2008. Soft peer review: social software and distributed scientific evaluation. In P. Hassanaly et al., eds. Proceedings of the 8th International Conference on the Design of Cooperative Systems, Carry-le-Rouet. Aix-en-Provence, France: Institut d?Etudes Politiques d?Aix-en-Provence, pp. 99?110.
Weller, K. & Peters, I., 2012. Citations in Web 2.0. Available at: http://nfgwin.uni-duesseldorf.de/sites/default/files/Weller.pdf.
Altmetrics and Other Novel Measures for Scientific Impact
- "a New Research Impact Measuring System" By Nader Ale Ebrahim
A new research impact measuring systemNader Ale Ebrahim, Research Support Unit, Centre of Research Services, IPPP, University of Malaya (UM), Kuala Lumpur, Wilayah Persekutuan 50603 AbstractFor years, scientists have been trying to measure the quality...
- Impact Of Social Sciences ? Enter Alternative Metrics: Indicators That Capture The Value Of Research And Richness Of Scholarly Discourse
Source: http://blogs.lse.ac.uk/impactofsocialsciences/2015/10/12/enter-alternative-metrics/ Enter Alternative Metrics: Indicators that capture the value of research and richness of scholarly discourseMany scholars have begun to turn to alternative...
- Journal & Author Impact Metrics | University Of Texas Libraries
Source: http://www.lib.utexas.edu/subject/education/journalmetrics Journal & Author Impact Metrics Journal Impact Factor (JIF) What it is: A measure of citations to a journal based on 2 year period. A 2012 impact factor...
- Casesblog - Medical And Health Blog: The Number Of Tweets Predicts Future Citations Of A Specific Journal Article
Source: http://casesblog.blogspot.com/2012/03/number-of-tweets-predicts-future.html The Number of Tweets Predicts Future Citations of a Specific Journal Article Citations of journal articles and the impact factor are widely used measures of scientific...
- Do More Tweets Mean Higher Citations?
Source: http://blogs.lse.ac.uk/impactofsocialsciences/2012/02/09/more-tweets-more-citations/ Do more tweets mean higher citations? If so, Twitter can lead us to the ?personalised journal?; pinpointing more research that is relevant to your interests....
Social Sciences
Altmetrics and Other Novel Measures for Scientific Impact
Source: http://book.openingscience.org/vision/altmetrics.html
Altmetrics and Other Novel Measures for Scientific Impact
Martin FennerAbstract
Impact assessment is one of the major drivers in scholarlycommunication, in particular since the number of available faculty
positions and grants has far exceeded the number of applications. Peer
review still plays a critical role in evaluating science, but
citation-based bibliometric indicators are becoming increasingly
important. This chapter looks at a novel set of indicators that can
complement both citation analysis and peer review. Altmetrics use
indicators gathered in the real-time Social Web to provide immediate
feedback about scholarly works. We describe the most important
altmetrics and provide a critical assessment of their value and
limitations.
Good science, original work, always went beyond the body of received
opinion, always represented a dissent from orthodoxy. However, then,
could the orthodox fairly assess it? Richard Rhodes mod. from Michael Polanyi in ?Making of the Atomic Bomb?
Introduction
Impact assessment of researchers and their research is central toscholarly communication. In the last 25 years, we have seen a shift from
individual qualitative assessment by peers to systematic quantitative
assessment using citation analysis of journal articles. Arguably the
impact of research can not be quantified, and citation analysis falls
short of a comprehensive analysis, but the journal as a filter for
relevant scholarly content and the Journal Impact Factor as a tool to
quantify the relevance of journals are at the core of how research is
communicated and evaluated today.
The central role of the journal (to distribute, filter, and help
evaluate scholarly content) has dramatically changed with the shift from
print to electronic publishing, and is no longer appropriate for the
assessment of impact. We can look at citations of individual articles,
and at other measures of impact using usage stats and the Social Web.
Moreover, impact assessment does not have to be confined to journal
articles; research outputs such as data publication can also be
assessed.
Altmetrics is a young discipline that looks at new metrics based on
the Social Web for analyzing scholarship. Altmetrics are complementary
to the citation-based filters which we have relied upon for the past 50
years and try to overcome some of their shortcomings: citations are slow
to accumulate, and often miss new forms of scholarly content such as
datasets, software, and research blogs (Priem et al. 2012a).
Altmetrics are challenging this established system, and are therefore
seen by many as either an opportunity or a threat to the current system
of scholarly communication. This potential makes altmetrics both
fascinating and challenging, as many discussions about altmetrics are
often intermixed with other ideas about how to change scholarly
communication.
Terminology
Scientometrics is the science of measuring and analysing science.Bibliometrics is a major subdiscipline of
scientometrics which measures the impact of scientific publications.
Citation analysis is the most popular application of bibliometrics.
Usage-based metrics use usage data (pageviews,
document downloads, etc.) to assess scholarly impact. The concept was
popularized by the COUNTER (Counting Online Usage of NeTworked
Electronic Resources) and MESUR (MEtrics from Scholarly Usage of
Resources) projects.
Altmetrics is the creation and study of new metrics based on the Social Web for analyzing and informing scholarship (Altmetrics Manifesto).
Altmetrics is a sub-discipline of scientometrics. Altmetrics typically
looks at individual research outputs, including journal articles or
datasets.
Article-level metrics are a comprehensive and multidimensional suite of transparent and established metrics at the article level (see PLOS Article-Level Metrics).
They collect and provide metrics for individual articles, rather than
aggregating them per journal. Article-level metrics include citations,
usage data, and altmetrics. Article-level metrics are typically
associated with the publisher Public Library of Science (PLOS), who
introduced them for all of their articles in 2009. Altmetrics and
article-level metrics are sometimes used interchangeably, but there are
important differences:
- Article-level metrics also includes citations and usage data
- Altmetrics can also be applied to other research outputs, such as research data
Author-level metrics aggregate the metrics of all research by a specific author. Metrics can also be aggregated by institution, discipline, etc.
Post-publication peer review is the process whereby
scientific studies are absorbed into the body of knowledge (BMJ Group
2011). This definition is much broader and does not just include
activities that are traditionally described as peer review. In contrast
to metrics, the focus is on the discussion of a paper in comments, blog
posts, and citations. A broader term with similar meaning is
post-publication activity.
History
In 2008 Dario Taraborelli published a paper on soft peer review,advocating social bookmarking tools for post-publication peer review.
Neylon and Wu described the PLOS Article-Level Metrics service launched
in 2009 in an article published the same year. Priem and Hemminger
published an article in July 2010 that describes scientometrics 2.0 and
called for new metrics based on Web 2.0 tools. Groth and Gurney (???)
studied chemistry science blogging about scholarly papers and presented
their findings at the Web Science Conference 2010. The Altmetrics
manifesto was published in October 2010 by Jason Priem, Dario
Taraborelli, Paul Groth and Cameron Neylon.
ReaderMeter is a web service that tracks the number of Mendeley
readers of all papers of a particular author. ReaderMeter was launched
in late 2010 and is the first working altmetrics service. The first
altmetrics workshop was was altmetrics11, held at the ACM Web Science Conference 2011 Workshop
in June 2011. Hackathons are an important part of altmetrics history: a
working prototype for Total Impact (now ImpactStory) was put together
at the Beyond Impact conference in May 2011, and the idea of the
ScienceCard project started at the Science Online London conference in
September 2011. Three of the 11 finalists of the Mendeley/PLOS Binary
Battle programming contest in September 2011 were altmetrics
applications. In 2012, we saw the launch of several altmetrics services,
more publishers implementing altmetrics for their journal articles, and
an increasing number of presentations and workshops dedicated to
altmetrics.
Scholarly research
Two workshops dedicated to altmetrics research and associated withthe ACM Web Science conference were held: June 2011 in Koblenz, Germany
and June 2012 in Evanston, IL.
PLOS ONE launched the Altmetrics collection in October 2012, with initially 7 research articles published since June 2009.
Much early altmetrics research has examined reference managers,
particularly Mendeley and CiteULike. Li et al. (2011) found 92% of
Nature and Science articles in their sample had been bookmarked by one
or more Mendeley users, and 60% by one or more CiteULike users. Bar-Ilan
(2012) showed 97% coverage of recent JASIST articles in Mendeley.
Priem, Piwowar and Hemminger (2012) reported that the coverage of
articles published in the PLOS journals was 80% in Mendeley and 31% in
CiteULike. Sampling 1,397 F1000 Genomics and Genetics papers, Li and
Thelwall (2012) found that 1,389 of those had Mendeley bookmarks.
Studies have consistently found moderate correlation between
reference manager bookmarks and Web of Science (WoS) citations. Li et
al. (2011) showed r=0.55 of Mendeley and r=0.34 of CiteULike readers
with WoS citations respectively. Weller and Peters (2012) report similar
correlation values for a different article set between Mendeley,
CiteULike, BibSonomy, and Scopus. Bar-Ilan (2012) found a correlation of
r=0.46 between Mendeley readership counts and WoS citations for
articles in JASIST. User-citation correlations for sampled Nature and
Science publications were 0.56 (Li et al. 2011); Priem et al. (2012b)
report a correlation of 0.5 between WoS citations and Mendeley users
articles published by the open-access publisher PLOS.
Twitter has also attracted significant interest from altmetrics researchers. Priem and Costello (2010) and Priem et al. (2011) report that scholars use Twitter as a professional medium for discussing articles, while Eysenbach (2011)
found that highly-tweeted articles were 11 times more likely become
highly-cited later. Analyzing the use of Twitter during scientific
conferences, Weller and Puschmann (2011)
and Letierce et al. (2010) report that there was discipline-specific
tweeting behavior regarding topic and number of tweets, as well as
references to different document types including journal articles,
blogs, and slides. Other sources have examined additional data sources
besides reference managers and Twitter, investigating examined citation
from Wikipedia articles (Nielsen 2007) and blogs (???; Shema et al. 2012) as sources of alternative impact data.
Use cases
Altmetrics can complement traditional bibliometrics and are more appropriate in a number of scenarios:- Metrics as a discovery tool
- Data-driven stories about the post-publication reception of research
- Business intelligence for a journal, university or funder
- Evaluation of the impact of research and researchers
Metrics as a discovery tool
Information overflow has become a major problem, and it has becomeclear that relying on the journal as a filter is no longer an
appropriate strategy. Altmetrics have the potential to help in the
discovery process, especially if combined with more traditional
keyword-based search strategies, and with the social network information
of the person seeking information. The advantage over citation based
metrics is that we don?t have to wait years before we can see meaningful
numbers. The free Altmetric PLOS Impact Explorer
is an example for a discovery tool based on altmetrics and highlights
recently published PLOS papers with a lot of social media activity.
Altmetric.com also provides a commercial service for content from other
publishers.
Data-driven stories about the post-publication reception of research
Altmetrics can help researchers demonstrate the impact of theirresearch, in particular if the research outputs are not journal
articles, but data sets, software, etc., and if the impact is best
demonstrated in metrics other than citations. ImpactStory
focuses on this use case. Often creators of web-native scholarly
products like datasets, software, and blog posts are hard pressed to
demonstrate the impact of their work, given a reward system built for a
paper-based scholarly publishing world. In these cases, ImpactStory
helps to provide data to establish the impacts of these products and
allow forward-thinking researcher. ImpactStory also gathers altmetrics
to demonstrate wider impacts of traditional products, tracking their
impact through both traditional citations and novel altmetrics.
Business intelligence for a journal, university or funder
The focus is not on the individual article, but rather on overalltrends over time and/or across funding programs, disciplines, etc. This
is an area that the typical researchers is usually less interested in,
but is important for strategic decisions by departments, universities,
funding organizations, publishers, and others. This area has been
dominated by large commercial bibliographic databases such as Web of
Science or Scopus, using citation data. Plum Analytics is a new service that also provide altmetrics and is focusing on universities. The publisher PLOS makes a comprehensive set of citations, usage data and altmetrics available for all articles they published.
Altmetrics as an evaluation tool
Traditional scholarly metrics are often used as an evaluation tool,including inappropriate uses such as using the Journal Impact Factor to
evaluate publications of individual researchers. Before altmetrics can
be used for evaluation, the following questions need to be addressed:
- Can numbers reflect the impact of research, across disciplines and over time?
- Does the use of metrics for evaluation create undesired incentives?
- Do the currently available altmetrics really measure impact or something else?
- How can we standardize altmetrics?
- How easily can altmetrics be changed by self-promotion and gaming?
scientometrics for evaluation, whereas the last three questions are more
specific for altmetrics. All these issues can be solved, but it will
probably take some time before altmetrics can be reasonably used for
evaluation.
Author-level metrics can also include citations and usage stats.
Citations are a more established metric for impact evaluation, and
citations based on individual articles are much more meaningful than the
metrics for the journal that a researcher has published in. The
Hirsch-Index (or h index, Hirsch 2005) is a popular metric to quantify
an individual?s scientific research output. The h index is defined as
the number of papers with citation number ?h, e.g. an h index of 15 means a researcher has published at least 15 papers that have been cited at least 15 times.
Example metrics and providers
A growing number of metrics are used by the altmetrics community, andthe most important metrics and providers are listed below. Not all
metrics measure scholarly impact, some of them are indicators of
attention, and in rare cases self-promotion. Some metrics are good
indicators of activity by scholars (e.g. citations or Mendeley
bookmarks), whereas other metrics reflect the attention by the general
public (e.g. Facebook or HTML views).
| Scholars | Public | |
| Discussed | science blogs, journal comments | Blogs, Twitter, Facebook, etc. |
| Recommended | Citations by editorials, Faculty of 1000 | Press release |
| Cited | Citations,full-text mentions | Wikipedia mentiones |
| Saved | CiteULike, Mendeley | Delicious Facebook |
| Viewed | PDF downloads | HTML views |
initial activity of reading the abstract and downloading the paper,
whereas citations are the result of much more work, they therefore
account for less than 0.5% of all HTML views. Altmetrics tries to
capture the activities that happen between viewing a paper and citing
it, from saving an article to informal online discussions.
Mendeley
Mendeley is one most widely used altmetrics services - the number ofarticles with Mendeley bookmarks is similar to the number of articles
that have ciations. Mendeley provides information about the number of
readers and groups. In contrast to CiteULike no usernames for readers
are provided, but Mendeley provides basic information regarding
demographics such as country and academic position. Mendeley is a social
bookmarking tool used by scholars and the metrics probably reflect an
important scholarly activity - adding a downloaded article to a
reference manager.
CiteULike
CiteULike is another social bookmarking tool, not as widely used asMendeley and without reference manager functionality. One advantage over
Mendeley is that usernames and dates for all sharing events are
publicly available, making it easier to explore the the bookmarking
activity over time.
they are only stored for short periods of time (typically around 7
days). There is a lot of Twitter activity around papers, and only a
small fraction is from the authors and/or journal. With some journals up
to 90% of articles are tweeted, the number for new PLOS journal
articles is currently at about 50%. The Twitter activity typically peeks
a few days after publication, and probably reflects attention rather
than impact.
content, and provides a wider variety of interactions (likes, shares and
comments). Facebook activity is a good indicator for public interest in
a scholarly article and correlates more with HTML views than PDF
downloads.
Wikipedia
Scholarly content is frequently linked from Wikipedia, covering about 6% of all journal articles in the case of PLOS. TheWikipedia Cite-o-Meterby Dario Taraborelli and Daniel Mietchen calculates the number of
Wikipedia links per publisher. In the English Wikipedia the most
frequently cited publisher is Elsevier with close to 35,000 links. In
addition to Wikipedia pages, links to scholarly articles are also found
on user and file pages.
Science Blogs
Blog posts talking about papers and other scholarly content aredifficult to track. Many science bloggers use a blog aggregator,
Research Blogging, Nature Blogs and ScienceSeeker being the most popular
ones. The number of scholarly articles discussed in blog posts is small
(e.g. less than 5% of all PLOS articles), but they provide great
background information and can sometimes generate a lot of secondary
activity around the original paper (both social media activity and
downloads).
Altmetrics service providers
Comprehensive altmetrics are currently only available from a smallnumber of service providers. This will most likely change in the near
future, as more organizations become interested both in analyzing
altmetrics for their content (publishers, universities, funders) or for
providing altmetrics as a service.
The open access publisher Public Library of Science (PLOS)
was the first organization to routinely provide altmetrics on a large
number of scholarly articles. The first version of their article-level
metrics service was started in March 2009, and PLOS currently provides
usage data, citations and social web activity from 13 different data
sources. The article-level metrics data are provided via an open API and as monthly public data dump.
Altmetric.com is a commercial start-up that started
in July 2011. They maintain a cluster of servers that watch social media
sites, newspapers and magazines for any mentions of scholarly articles.
The data are available to individual users and as service for
publishers.
ImpactStory is a non-profit service providing
altmetrics since late 2011. They provide both altmetrics and traditional
(citation) impact metrics for both traditional and web-native scholarly
products, and are designed to help researchers better share and be
rewarded for their complete impacts.
Plum Analytics is a start-up providing altmetrics
data to universities and libraries. They also provide usage stats and
citation data, and track research outputs beyond journal articles,
e.g. presentations, source code and datasets.
At this time it is unclear how the altmetrics community will develop
over the next few years. It is possible that one or a few dominant
commercial players emerge similar to the market for citations, that a
non-profit organization is collected these numbers for all stakeholders,
or that we see the development of a more distributed system with data
and service providers, similar to how usage data for articles are
distributed.
Challenges and Criticism
Many challenges remain before we can expect altmetrics to be morewidely adopted. A big part of the challenge is the very nature of the
Social Web, which is much more difficult to analyze than traditional
scholarly citations.
- the constantly changing nature of the Social Web, including the lack of commonly used persistent identifiers
- self-promotion and gaming, inherit to all Social Web activities, and
aggravated by the difficulty of understanding who is talking - Altmetrics is more interested in things that can be measured, rather
than things that are meaningful for scholarly impact. We therefore
measure attention or self-promotion instead of scholarly impact.
altmetrics, but are hard to solve for evaluation tools. Altmetrics is
still a young discipline and the community is working hard on these and
other questions, including standards, anti-gaming mechanisms, and ways
to put metrics into context.
References
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Bar-Ilan, J., 2012. JASIST@mendeley, Available at: http://altmetrics.org/altmetrics12/bar-ilan/.
ImpactStory, 2012. A new framework for altmetrics. ImpactStory blog. Available at: http://blog.impactstory.org/2012/09/14/31524247207/.
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